Editors' Cuts

The Age of Data

Bill Kenealy
Insurance Experts' Forum, January 20, 2012

While mobile, social and consumer-derived technologies in general seem to be garnering an inordinate amount of mind share in the technology press lately, the reality is that they are still peripheral to the business of insurance.

As much as I wish 55-inch OLED televisions, Ultrabooks or all the other cool stuff on display last week at the Consumer Electronic Show in Las Vegas was germane to insurance and our editorial mission, it just isn't. (If, by some odd chance it is, please, please drop my editors a note. January is a freezing mess here in Chicago). However, if there is one technology germane to insurance that has the “wow factor,” it is predictive analytics. 

While not necessarily a new technology, broader use of predictive analytics throughout the insurance enterprise paired with incredible advances in the hardware and software that enables it, points to something of great import not just for insurers, but other industries as well. A recent article in the Wall Street Journal, “So, What's Your Algorithm?” traces the newfound cachet of analytics from Wall Street to Moneyball. "Call it Big Data, analytics, or decision science," the article states. "Over time, this will change your world more than the iPad 3."

One way to quantify the analytics explosion may be to take a peak at the bottom line of a company synonymous with the technology, SAS Institute. This week the company reported 12-percent annual top-line growth, achieving record global revenue of US$2.725 billion in 2011. This number is all the more impressive when one considers revenues were in the $1 billion range a decade ago.

Jim Davis, SVP and chief marketing officer for SAS, credits a variety of factors for the technology's growth. While the company has seen a boom in demand in sectors such as government, utilities and manufacturing, financial services firms still account for 40 percent of revenue for SAS.

"More people at the executive level understand what PA can do for their organizations," Davis tells me. "Hence the growth in areas such as fraud detection and risk."

Davis also credits increasing utilization of ever-improving hardware for improving the visibility and viability of analytics. Inexpensive server blades containing powerful multi-core processors have greatly reduced the cost and time of running even the most complex of analytic calculations. Thus, insurers are now able to analyze all data in a given database rather than a subset of it. "We are using high-performance computing to reduce the latency in decision-making," he says. "We are taking industry standard servers and seeing incredible results."

Another technology trend catalyzing broader use of analytics is cloud computing. SAS built a dedicated cloud facility on its Cary, N.C., campus that went online in mid-2010. "Our hosted revenue is up 48 percent," Davis says. "It's becoming a big business for us. What started off as a pet project a few years ago has grown in leaps and bounds."

One insurance-specific driver of demand for predictive tools is telematics, which marries analytics to mobility and has the potential to revolutionize insurance processes from underwriting to claims. "I wonder if people realize how much data is going to be derived from telematics and what the potential is for predictive analytics," he concludes. "If telematics takes off, it's really going to be Big Data. You are going to have to have the technology platforms to make sense of it.”

Bill Kenealy is a senior editor for Insurance Networking News.

Readers are encouraged to respond to Bill by using the “Add Your Comments” box below. Healso can be reached at william.kenealy@sourcemedia.com.

This blog was exclusively written for Insurance Networking News. It may not be reposted or reused without permission from Insurance Networking News.

Comments (3)

Nice work Bill.

Though a little detail on telematics would have made the entry more complete. I took a cue from this article and have expanded on your contents (I come from an applied analytics background).

Link: http://dataceptive.wordpress.com/2012/01/29/insurance-data-and-telematics/

Posted by: abhay t | January 29, 2012 2:21 AM

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While many fraud technologies are reactive. At SAS we have found that customers who use our Fraud Framework solution have been able to detect organized fraud rings months before traditional solutions, thereby enabling insurers to save millions of dollars on fraudulent claims. Here is a great article on fighting fraud using analytics - http://www.insurancenetworking.com/issues/2008_77/fighting-fraud-siu-29446-1.html

Posted by: stuart.rose | January 24, 2012 2:51 PM

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Du jour is the best way to describe the current fascination with large scale analytics. What SAS, IBM and other apostles haven't told you is the that the resources needed to implement these tools are far greater than advertised, their accuracy will vary based on external factors, and in healthcare, they offer minimal preventive value for stopping fraud and abuse.

It doesn't require Big Data to see that a certain surgeon is performing 3 times the angioplastys as his cohort group. And it may be legitimate. Unfortunately, the biggest problem in using these tools for healthcare fraud is that they offer no preventive value, quite the contary- a pattern of abuse has to be established for these tools to even work. By that time, the money has been paid and the crooks are gone. Catch -22 anyone?

Posted by: JEFF L | January 23, 2012 3:25 PM

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